Abstract
The global warming potential (GWP) is widely used in policy analysis, national greenhouse gas (GHG) accounting, and technology life cycle assessment (LCA) to compare the impact of non-CO2 GHG emissions to the impact of CO2 emissions. While the GWP is simple and versatile, different views about the appropriate choice of time horizon—and the factors that affect that choice—can impede decision-making. If the GWP is viewed as an approximation to a climate metric that more directly measures economic impact—the global damage potential (GDP)—then the time horizon may be viewed as a proxy for the discount rate. However, the validity of this equivalence rests on the theoretical basis used to equate the two metrics. In this paper, we develop a new theoretical basis for relating the GWP time horizon and the economic discount rate that avoids the most restrictive assumptions of prior studies, such as an assumed linear relationship between economic damages and temperature. We validate this approach with an extensive set of numerical experiments using an up-to-date climate emulator that represents state-dependent climate-carbon cycle feedbacks. The numerical results largely confirm the theoretical finding that, under certain reasonable assumptions, time horizons in the GWP of 100 years and 20 years are most consistent with discount rates of approximately 3% and 7% (or greater), respectively.
Highlights
Climate metrics are widely used in policy analysis, national greenhouse gas (GHG) accounting, and technology life cycle assessment (LCA) to convert emissions of non-CO2 GHGs into CO2-equivalent units
This study makes three important contributions to the literature on climate metrics. It provides a theoretical basis relating the global warming potential (GWP) and global damage potential (GDP) that is less restrictive than prior theoretical formulations
Using the newly developed theoretical basis, this study shows that the choice of time horizon in the GWP can be directly related to the choice of discount rate or other fundamental economic parameters
Summary
Climate metrics are widely used in policy analysis, national greenhouse gas (GHG) accounting, and technology life cycle assessment (LCA) to convert emissions of non-CO2 GHGs into CO2-equivalent units. Prior studies offering a theoretical basis for the approximate equivalence between the GWP and GDP (upon which the numerical studies conceptually rely) make several strong assumptions Both Tol et al (Tol et al 2012) and Marten and Newbold (Marten and Newbold 2012) show that the GWP approximates the GDP if the discount rate is assumed to be zero, the time horizon of the GDP is set equal to that of the GWP, and damages are assumed to vary linearly with temperature. This set of assumptions is quite restrictive. We utilize a climate emulator capable of capturing climate-carbon cycle feedbacks (Millar et al 2017; The National Academies 2017; Smith et al 2018) to numerically validate the theory across a wide range of climate and economic assumptions, including baseline emissions scenario, representation of climatecarbon cycle feedbacks, methane lifetime, equilibrium climate sensitivity (ECS), damage function exponent, and the economic growth trajectory
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